SQL School

#Fabric Data Engineer

Fabric Data Engineer Data Engineer is the latest trending job role that deals with End to End Data Warehouse design (DWH) using ETL (Extract, Transform, Load) techniques. This prominent job role also involves Big Data Analytics and Business Intelligence implementation using Spark, PySpark, Cloud Computing, TSQL and more..

In this course, we also aim at optimized One Lake Structures (Warehouse, LakeHouse, Stream House, etc.. ) and big data analytics using KQL, Activator and more.. !

Training Schedules

S No	Time (IST, Mon - Fri)	Start Date
1	6 AM - 7 AM	Aug 6th
2	10 AM - 11 AM	Aug 26th
3	11 AM - 12 PM	Aug 12th
4	8 PM -9 PM	Aug 18th

Fabric Data Engineer
Training Course Contents:

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Module 1 : Microsoft SQL (TSQL)

Ch 1: SQL SERVER INTRODUCTION

Database Introduction
Types of Databases
Need for & ETL, DWH
BI Implementations
SQL Server Advantages
Version, Editions of MSSQL
Data Analyst Job Roles

Ch 2: SQL SERVER INSTALLATIONS

SQL Server 2019, 2017
SSMS Tools Installation
Database Engine (OLTP)
SCM, Configuration Tools
Instance Types, Uses
Authentication Modes
Collation, File Stream

Ch 3: SQL BASICS – 1

Need for Databases, Tables
Need for SQL Commands
DDL, DML & DQL Statements
Database Creation @ GUI
Data Operations @ GUI
Session ID, SQL Context
DB, Tables, Data @ SQL

Ch 4: SQL BASICS – 2

DDL Variants in MSSQL
DML Variants in MSSQL
INSERT & INSERT INTO
SELECT & SELECT INTO
Basic Operators in SQL
Special Operators in MSSQL
ALTER, ADD, TRUNCATE, DROP

Ch 5: Data Imports, Schemas

Data Imports with Excel
ORDER BY & UNION
UNION ALL For Sorting Data
Creating, Using Schemas
Real-world Banking Database
Table Migrations @ Schemas
2 Part, 3 Part & 4 Part Naming

Ch 6 : Constraints, Index Basics

Need for Constraints, Keys
NULL, NOT NULL, UNIQUE
Primary Key & Foreign Key
RDBMS and ER Models
Identity Property, Default
Clustered Index, Primary Key
Non Clustered Index, Unique

Ch 7: Joins & Views Basics

JOINS: Purpose. Inner Joins
Left / Right / Full Outer Joins
Cross Joins, Query Tuning
Creating & Using Views
DML, SELECT with Views
RLS : WITH CHECK OPTION
System Views & Metadata

Ch 8: Functions(UDF), Data Types

Using Functions in MSSQL
Scalar Value Functions
Inline & Multiline Functions
Date & Time Functions
String, Aggregate Functions
Data Types : Integer, Char, Bit
SQL Variant, Timestamp, Date

Ch 9: Stored Procedures,Models

Stored Procedures & Usage
Creating, Testing Procedures
Encryption, Deferred Names
SPs for Validations, Analysis
System SPs, Recompilation
Normal Forms & Types
Data Models, Self-References

Ch 10: Triggers, Temp Tables

Need for Triggers
DDL & DML Triggers
Using Memory Tables
Data Replication, Automation
Local & Global Temp Tables
Testing & Using Temp Tables
SELECT .. INTO & Bulk Loads

Ch 11: DB Architecture, Locks

Planning VLDBs : Files, Sizing
Filegroups, Extents & Types
Log Files : VLF, Mini LSN
Table Location, Performance
Schemas, Transfer, Synonyms
Transactions Types, Lock Hint
Query Blocking Scenarios

Ch 12 : Cursors & CTEs, Links

Cursors : Realtime Use
Fetch & Access Cursor Rows
CTEs for SELECT, DML
CTEs: Scenarios & Tuning
Linked Servers, Remote Joins
Linked Servers: MSDTC, RPC
Tuning Remote Queries

Ch 13: Merge, Upsert & Rank

Need for Merge in ETL
Incremental Loads with SQL
MERGE and RANK Functions
Window Functions, Partition
Identify, Remove Duplicates

Ch 14: Grouping & Cube

Group By & HAVING
Cube, Rollup & Grouping
Joins with Group By
3 Table, 4 Table Joins
Query Execution Order

Ch 15: Self Joins, Excel Analysis

Self Joins & Self References
UNION, UNION ALL
Sub Queries with Joins
IIF, CASE, EXISTS Statements
Excel Analytics, Pivot Reports

Module 2: Fabric Data Engineer

Ch 1: Fabric Introduction

Need for Fabric, Big Data
Fabric Data Engineering Model
Fabric Components (Items)
Microsoft Fabric: Advantages
Cloud Warehouse Uses
Benefits of Fabric Over Azure
Azure Versus Fabric DWH

Ch 2: Fabric Account, Workspace

Need for Fabric Workspace
Workspace Creation Process
Pins and New Items
Item Categorization
ETL, Storage, Analytical
Streaming, Monitoring
Compute & Separation

Ch 3: Fabric Architecture

Intelligent Data Foundation
Polaris Distributed Engine
Stateless & Stateful
Cache, Metadata, Xact & Data
Fabric Tasks, Inputs & DAG
State Machine & Statistics
Hot Spot Recovery

Ch 4: Fabric Warehouse

Fabric Warehouse Creation
Fabric Warehouse Features
Fabric Warehouse Properties
Fabric Warehouse Limitations
DWH Internal Operations
Default Schemas & Objects

Ch 5: Fabric Data Types

Realtime use of Fabric Houses
Exact, Approximate Numbers
Date and Time Data Types
Fixed & Variable Length
Binary & String Data Types
Fabric Type Limitations

Ch 6: SSMS Connections

Warehouse SQL Connection
Database Engine Server
Multi Factor Authentication
Warehouse Artifacts
Executing .SQL Scripts
Testing Fabric Artifacts

Ch 7: Fabric Caching

Fabric Caching Process
In-memory Cache, Disk Cache
Cache Types: LRU /MRU
Cold Cache / Cold Run
Realtime use of Caching
Performance Advantages
Warehouse Optimizations

Ch 8: Fabric Statistics

Query Engine Options
Statistics Types
Leverage Statistics
Auto, Manual Statistics
Update Statistics
Statistics Consistency
Statistics Lists & Reports

Ch 9: Time Travel

Continuous Data Protection
Data Storage, Retention
FOR TIMESTAMP AS OF
Time Travel Scenarios
Time Travel Implementation
Time Travel on Queries
Time Travel Limitations

Ch 10: Aggregated Data Store

Options for Data Aggregations
Save As table, Save As View
Single Table Aggregations
Multi Table Aggregations
Dynamic Conditions
Parameterized Aggregations

Ch 11: Zero Copy Cloning

User Layer, Storage Layer
Cloning & Parquet Files
Synapse Data Warehouse
Data History Retention
Point In Time , Schema Level
Zero Copy Cloning Limitations

Ch 12: Fabric Security

Workspace Security
Warehouse Security
Item Security & Roles
Adding AD Users
Item Security Limitations
MFA & Client Security

Ch 13: Fabric Data Factory

ETL Implementation Options
Need for Fabric Data Factory
ETL Operations in FDF
Data Sources, Transformations
Data Destinations (Sinks)
Creating Pipelines

Ch 14: Fabric Pipelines

Activities and Connections
Gateways & OnPrem Access
Data Sets & Activity Sets
Data Activator & Alerts
Run ID & Monitoring
Pipeline Creation, Verification
Activity Check, Schedule

Ch 15: Fabric Pipelines Design

Creation Options for Pipelines
Azure SQL DB Data Loads
Creating Data Sets
RRR Transformations
Copy Command Usage
Internal Staging (Workspace)
Data Loads to FDWH

Ch 16: Fabric Aggr Data Loads

Aggregation Scenarios
Creating Views in TSQL
Using Views in FDF Pipelines
Using Pipeline Editor
Data Loads to Warehouse
Pipeline Verifications

Ch 17: ETL Staging

Staging : Advantages
Caching & Storing Concept
Staging Types in Fabric
Workspace & External
External Stages in Pipelines
Compressions & Advantages
Pipeline Trigger, Monitor

Ch 18: OnPrem Gateways

Need for On_Premi Gateway
Installing & Configuring
Authentication, Usage
OnPremises Connections
Pipelines for Data Loads
Warehouse Data Storage
Data Refresh with Gateways

Ch 19: Fabric Lakehouse

Need for Fabric Lakehouse
Files and Tables Storage
Data Sources: Parquet Files
Transformation Options
Direct Lake Concepts
Lakehouse Consumption
Lakehouse Real time Use

Ch 20: Lakehouse File Loads

Creating Lakehouse
Copy Data Wizard
Azure SQL Database Source
File Data Loads in Lakehouse
Concurrency & Batch Count
Pipeline Execution Tests
Pipeline Monitor Check

Ch 21: Lakehouse Aggr Loads

Aggregated Data Store
Plan & Design Aggregations
Testing Aggregations
Pipelines for Data Compute
Data Copy Options
Pipeline Optimizations
Data Loads and Verification
Pipeline Execution Tests
Pipeline Monitor Check

Ch 22: MultiTable Loads in LH

Table Loads Connections
Data Load in Lakehouse
Using Copy Data Wizard
Data Store in Lakehouse
View Run History, Executions
SQL End Points & Access
Lakehouse Schemas

Ch 23: Lakehouse Visual Queries

Visual Query Interface
Visual Editor & Tables / Views
Merge, Remove, Sort Tfns
Data Preview, Save As Table
Save As View : Advantages
Using Schemas, Identifiers
TDS Packets & Transfer Units

Ch 24: File Explorer

Installing One Lake Explorer
Autocreation of Folders
Workspace Directories
Warehouse Directories, Logs
Lakehouse Folders, Files
Lakehouse Uploads
Explorer Tool Limitations

Ch 25: Power Query Level 1

Power Query Concept
Need for Power Query
Data Flow Gen 1
Data Flow Gen 2
Power Query Items
Differences with Copy Activity
ETL, ELT Process

Ch 26: Power Query Level 2

Data Flow Gen2 Operations
PQ Online Editor
Working with Binary Content
Detailed Data Options
Data Cleansing Options
Step Names, Aggregations
Warehouse Data Loads

Ch 27: Power Query Level 3

Binding Power Query Steps
Edit / Delete Steps
Optimizing Power Query
ETL & ELT with Power Query
Advanced Editor
M Language Expressions
Duplicate / Reference Queries

Ch 28: Fabric Notebooks

Need for Notebooks
Fabric Notebook Types
Get / Prep / Analyze
Sessions, Markdown Folding
Standard, High Concurrency
Magic Command
Freeze Cells

Ch 29: Spark SQL Notebooks

Creating Environment
Creating Spark Clusters
Spark Cluster Compute
SQL Analytics in Notebooks
Visual Query Vs SQL
Cell Execution Options
Magic Command Usage

Ch30: PySpark Notebooks

Creating / Using Environment
PySpark Notebook Sessions
Reading Source Data
Data Prep & Aggregations
Data Loads, Analytics
Cell Execution Options
Markdown Cells

Ch 31: StreamHouse, KQL

Need for Stream House
Auto creation of KQL
Manual KQL Databases
Verification & Usage
Differences with Warehouse
Differences with Lakehouse

Ch 32: KQL Query Sets

KQL Database ExtractionFile Imports – on Premises
Metadata Edit Options
Query Analytics
Exports, Visualizations
Query Sets Versus Notebooks

Ch 33: Fabric Data Activator

Need for Alerts, Notifications
Fabric Data Activator Options
Alert Conditions, Thresholds
Email Notifications
Events & Notifications
Edit / Enable / Disable

Ch 34: Model Layouts

Need for Layouts
Creating Model Layouts
Adding Refences, Keys
Power BI Semantic Models
Creating Report Items
Using Power BI Desktop

Ch 35: Azure Synapse Migrations

Azure Synapse DWH
Azure Synapse Connections
Migrating to Fabric
Compatibility Checks
Synapse Vs Fabric Warehouse
Fabric DWH Advantages

Ch 36: DP 700 Exam Guidance
End to End Realtime Project: Ecommerce Domain

Module 3: Power BI

Ch 1 : Power BI Introduction

Reporting Basics & Types
Interactive,Analytical Reports
Paginated Reports (RDL)
Power BI Eco System
Power BI Tools,Service,Server
Need for Power Query (M)
Need for DAX & Cloud

Ch 2: Power BI Basic Reports

Power BI Desktop Installation
Basic Report Design (PBIX)
Data View, Data Models
Data Points, Aggregations
Focus Mode, Spotlight, Exports
ToolTip, PBIX and PBIT
Visual Interactions & Edits

Ch 3 : Grouping, Hierarchies

Creating Groups in Power BI
Groups : Creation & Usage
Group Edits Options
Bins & Bin Size, Bin Count
Hierarchies: Creation, Use
Drill Down, Drill Up
Conditional Drill Down

Ch 4 : Visual Sync, Filters

Slicer & Single Select
Multi Select Options
Integer, Character Slicers
Visual Sync with Slicers
Filters: Visual, Page, Report
Drill Thru Filters & Usage
Basic, Top & Advanced
Clear Filter Options, Resets

Ch 5 : Bookmarks, Big Data

Bookmarks Creation & Usage
Visual Interactions, Bookmarks
Images : Actions, Bookmarks
Big Data Access with Power BI
Storage Modes: Direct Query
Import & Performance Impact
Formatting & Data Refresh
Summary, Date Time Formats

Ch 6 : Power BI Visualizations

Chart and Bar Visuals
Line and Area Charts
Maps, TreeMaps, HeatMaps
Funnel, Card, Multrow Card
PieCharts & Settings
Waterfall, Sentiment Colors
Scatter Chart, Play Axis
Infographics, Classifications

Ch 7 : Power Query Level 1

Power Query (Mashup)
ETL Transformations in PBI
Power Query Expressions
Table Combine Options
Merge, Union All Options
Table Transformations

Ch 8 : POWER QUERY LEVEL 2

Any Column Transformations
String / Text Transformations
Numeric Analytics & Mashup
Date Time Transformations
Add Column Transformations
Expressions and New Columns

Ch 9 : POWER QUERY LEVEL 3

Parameters in Power Query
Static Parameters, Defaults
Dynamic Dropdowns, Lists
Linking with Table Queries
Column From Examples
Step Edits, Type Conversions

Ch 10 : Power BI Cloud – 1

Power BI Cloud Concepts
Workspace Creation, Usag
Report Publish & Edits
Semantic Models in Realtime
Dashboard Creation, Usage
Clone, Share, Subscribe
Q&A, Lineage, Settings

Ch 11 : Power BI Cloud – 2

Data Gateways, Data Refresh
Data Source Configurations
Data Refresh & Scheduling
Gateway Optimizations
Semantic Model Optimizations
Report Optimizations
Dashboard Optimizations

Ch 12 : Power BI Cloud – 3

Power BI Apps, Shares
App Sections & Options
App Updates, Security
Excel Analytics
Data Explorer Option
Sharing, Subscriptions
Alerts, Metrics, Insights

Ch 13 : Report Server & DAX

Power BI Report Server
Report Database, TempDB
Web Service & Server URL
Paginated Reports (RDL)
Report Builder Tool Usage
DAX : Purpose, Realtime Use

Ch 14: DAX Level 2

DAX Measures Creation, Use
DAX Functions: IIF, ISBLANK
SUM, CALCULATE Functions
DAX Cheat Sheet : Examples
Quick Measures in Power BI
Running Totals, Filters

Ch 15 : DAX Level 3

Star Rating Calculations
Data Models & DAX
Star & Snowflake Schemas
Dimensions, Fact Tables
DAX Expressions & Joins
DAX Variables, Usage

Ch 16 : DAX Level 4

Dynamic Report with DAX
SELECTED MEMEBER
Time Intelligence with DAX
PARALLELPERIOD, DATE
DAX with Big Data
Big Data Analytics

Ch 17 : Realtime Project Phase 1

Project Requirement Spec
Understanding Data, Formats
Report Pattern Design
Report Design & Modelling
Power Query, DAX, Insights
Analytical Reports in Cloud

Ch 18 : Realtime Project Phase 2

Complete Project Solution
Project FAQs, Key Roles
Real-world Considerations
Power BI Admin Concepts
Resume Points, FAQs
PL 300 Exam Guidance

Fabric Data Engineer SQL School Sample Certificate

SQL SCHOOL

24x7 LIVE Online Server (Lab) with Real-time Databases.
Course includes ONE Real-time Project.

Fabric Data Engineer Training FAQ's

What is Fabric Data Engineer Job Role?

A Fabric Data Engineer is responsible for designing, building, and managing end-to-end data pipelines, modern data warehouses, and lakehouses using Microsoft Fabric. The role focuses on data ingestion, transformation, storage, governance, and security, enabling seamless analytics across the enterprise. Fabric Data Engineers work with Data Factory, Synapse Pipelines, Data Lake, and Warehouse/Lakehouse tools to ensure reliable, scalable, and optimized data solutions.

What are the Job Roles of a Fabric Data Engineer?

💼 Top Job Roles:

1️⃣ Build and orchestrate data pipelines using Fabric components
2️⃣ Manage modern data warehouse and lakehouse solutions
3️⃣ Implement data governance, lineage, and security
4️⃣ Optimize data storage, processing, and retrieval
5️⃣ Integrate diverse data sources (files, databases, APIs, IoT, etc.)
6️⃣ Collaborate with BI and analytics teams for end-to-end solutions and more..!

What does our Fabric Data Engineer Training course contain?

The course is carefully curated with below module:
👉🏻Module 1: MSSQL & TSQL Queries
👉🏻Module 2: Fabric Data Engineer
👉🏻Module 3: Power BI

Who can join this course?

Freshers aiming for data engineering careers
ETL developers transitioning to Microsoft Fabric
DBAs and BI developers moving to modern cloud data platforms
IT professionals seeking skills in Fabric-based data solutions
Anyone passionate about cloud data architecture
No prior coding experience is required. All concepts are taught from scratch

What training modes are available?

Option 1: LIVE Online Training (100% Interactive, step by step, assignments)

Option 2: Self Paced Videos (100% practical, step by step with concept wise assignments)

You may choose any one of these options, same curriculum!

I (Trainer) shall be available for doubts and clarifications, assignment check and review.

Why should I choose SQL School for Fabric Data Engineer training?

👉🏻 Every session is Practical, Step by Step with Concept wise FAQs !!

👉🏻 100% results with on-time practice. Daily Tasks for every session.

👉🏻 Concept wise tasks be submitted before next class for Job Waiters / Starters.

👉🏻 Concept wise tasks due for submission by Weekends for Working Professionals.

Why Choose SQL School

100% Real-Time and Practical
ISO 9001:2008 Certified
Concept wise FAQs
TWO Real-time Case Studies, One Project
Weekly Mock Interviews
24/7 LIVE Server Access
Realtime Project FAQs
Course Completion Certificate
Placement Assistance
Job Support
Realtime Project Solution
MS Certification Guidance